model_info.WrappedModel | R Documentation |
This generic function let user extract base information about model. The function returns a named list of class model_info
that
contain about package of model, version and task type. For wrappers like mlr
or caret
both, package and wrapper information
are stored
## S3 method for class 'WrappedModel'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'H2ORegressionModel'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'H2OBinomialModel'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'H2OMultinomialModel'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'scikitlearn_model'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'keras'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'LearnerRegr'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'LearnerClassif'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'GraphLearner'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'xgb.Booster'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'workflow'
model_info(model, is_multiclass = FALSE, ...)
## S3 method for class 'model_stack'
model_info(model, is_multiclass = FALSE, ...)
model |
- model object |
is_multiclass |
- if TRUE and task is classification, then multitask classification is set. Else is omitted. If |
... |
- another arguments |
Currently supported packages are:
mlr
models created with mlr
package
h2o
models created with h2o
package
scikit-learn
models created with scikit-learn
Python library and accessed via reticulate
keras
models created with keras
Python library and accessed via reticulate
mlr3
models created with mlr3
package
xgboost
models created with xgboost
package
tidymodels
models created with tidymodels
package
A named list of class model_info
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